Microbial and soil properties in bentgrass putting greens: Impacts of nitrogen fertilization rates

Microbial and soil properties in bentgrass putting greens: Impacts of nitrogen fertilization rates

Geoderma 162 (2011) 215–221 Contents lists available at ScienceDirect Geoderma j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c ...

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Geoderma 162 (2011) 215–221

Contents lists available at ScienceDirect

Geoderma j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / g e o d e r m a

Microbial and soil properties in bentgrass putting greens: Impacts of nitrogen fertilization rates Yueyan Liu a,b, Emily Dell b, Huaiying Yao a, Thomas Rufty c, Wei Shi b,⁎ a b c

Environmental and Resource Sciences, Zhejiang University, Hangzhou, 310029, PR China Department of Soil Science, North Carolina State University, Raleigh, NC 27695, USA Department of Crop Science, North Carolina State University, Raleigh, NC 27695, USA

a r t i c l e

i n f o

Article history: Received 8 May 2010 Received in revised form 24 October 2010 Accepted 20 February 2011 Keywords: Soil enzyme activity Microbial biomass C and N mineralization N fertilization Turfgrass

a b s t r a c t Nitrogen fertilization is important for maintaining the quality of golf course putting greens, but causes environmental concerns and affects soil organic matter buildup. Belowground biology and processes are vital to address both environmental and organic buildup issues. We examined microbial and soil properties in sand-based bentgrass putting greens that had been unfertilized or fertilized at the rates of 195, 244, and 305 kg N ha−1 yr−1 for over one year after turf establishment. Nitrogen fertilization increased soil organic C by ~ 10% and slightly modified microbial community as revealed by denaturing gradient gel electrophoresis, but had no effects on microbial biomass or C and N mineralization. We observed that changes in soil pH and enzyme activities were the functions of fertilization rates. Soil pH was reduced by ~ 0.3 to 0.8 units as fertilization rates increased. The activities of soil enzymes (β-glucosidase, N-acetyl-β-glucosaminidase, chitinase, and cellulase) were enhanced by fertilization at 195 or 244 kg N ha−1 yr−1, but was equivalent to or even lower than those in the unfertilized control when fertilization rate reached 305 kg N ha−1 yr−1. Results indicated that the activity of soil enzymes could be used as an important metric to diagnose the impacts of fertilization rates on soil. Fertilization rate at approximately 200 kg N ha−1 yr−1 appeared to be appropriate for managing putting greens. © 2011 Elsevier B.V. All rights reserved.

1. Introduction Turfgrass systems, especially golf courses, represent intensively managed ecosystems with high levels of fertilization, pesticide application, and irrigation. Although putting greens occupy only a small area of a golf course, they consume a disproportionate amount of resources, especially fertilizers (Schlossberg and Schmidt, 2007). Intensive N fertilization is essential for supporting and maintaining putting green quality including color, vigor, root-to-shoot ratio, and disease resistance (Turgeon, 1999). Two issues are often associated with N fertilization of putting greens. First, there are concerns over surface and ground-water pollution via N leaching or over the release of global warming gasses, N oxides via nitrification and denitrification. Best management practices, such as controls on the rate and the timing of fertilization and irrigation, may reduce leaching to minimal levels (Brauen and Stahnke, 1995; Johnston et al., 2003; Shuman, 2004). Second, N fertilization has been considered to cause the buildup of soil organic matter due to enhanced primary production and thus soil C input through root exudates as well as grass clippings. This buildup may ⁎ Corresponding author at: Department of Soil Science, North Carolina State University, Campus Box 7619, Raleigh, NC 27695, USA. Tel.: +1 919 513 4641; fax: +1 919 515 2167. E-mail address: [email protected] (W. Shi). 0016-7061/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.geoderma.2011.02.009

decrease water permeability, create anaerobic environment in the root zone, and thus damage putting green quality (Carrow, 2003). While soil microbial community is a vital component dictating soil N transformations and organic matter decomposition, its response to N fertilization has been overlooked in putting greens. Soil and microbial properties have been acknowledged as useful metrics for evaluating management impacts on soil sustainability and health. Often-used microbial attributes include microbial biomass, CO2 respiration, soil enzyme activity, and microbial community composition (Bandick and Dick, 1999; Biederbeck et al., 1987; Wolters, 1991; Wu and Brookes, 2005). Generally, an increase in microbial biomass and activity is thought to be beneficial to soil C and nutrient cycling and thus ecosystem productivity. In the case of N fertilization, multifaceted effects may simultaneously act on soil microbial community. Nitrogen fertilization may stimulate microbial growth and activity via its positive controls on primary production and thus soil organic C input (Liang and MacKezie, 1996; Raiesi, 2004). However, if N fertilization considerably increases soil osmotic tension and/or soil acidity, microbial biomass and activity may decline (Treseder, 2008; Yevdokimov et al., 2004). Nitrogen fertilization may also directly influence the physiology of microbial community and therefore its ability of organic matter decomposition. For example, when soil N availability is increased by fertilization, soil microbes may reallocate resource from producing N-

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acquiring enzymes to C- and other nutrient-acquiring enzymes (Sinsabaugh and Moorhead, 1994). It has been reported that in forest systems, N fertilization could stimulate C-acquiring enzymes such as cellulase and glucosidase but suppress oxidative enzymes such as phenol oxidase (Gallo et al., 2004; Saiya-Cork et al., 2002; Sinsabaugh et al., 2005). Such changes in soil enzyme activities have been found to be correlated with soil organic C dynamics in response to soil N availability (Carreiro et al., 2000; Waldrop et al., 2004). Furthermore, N fertilization may cause a shift in soil microbial community composition and subsequently alter microbial production of extracellular soil enzymes. The direction and magnitude of influences depend on microbial properties with some being more sensitive to N fertilization than others. Our previous research in a hay production field found that soil enzyme activity responded to N fertilization rates while CO2 respiration and N mineralization remained unaffected (Iyyemperumal and Shi, 2008). The objective of this study was to determine soil and microbial properties most responsive to the different rates of N fertilization in turfgrass putting greens. We hypothesized that, as in the hay production field (Iyyemperumal and Shi, 2008), soil enzymes were more responsive to the rates of N fertilization than other traditional microbial metrics. Because enzyme-catalyzed depolymerization is an important and perhaps rate-limiting step of organic matter decomposition, detection for the change of soil enzyme activity may facilitate an early prediction on potential change in soil organic matter. Thus, a better understanding on the impacts of N fertilization rates on soil microbial properties can help make informed management decisions to minimize organic matter buildup in putting greens. To better evaluate the impacts of fertilization rates on the putting green soil, the compositions of dissolved or extractable soil organic matter and microbial community were also included in the examination. 2. Materials and methods 2.1. Field plots and soil sampling Bentgrass putting greens were established in 2004 on sand-based topsoil made by mixing 10% peat and 90% sand, at Lake Wheeler Turfgrass Research Station, North Carolina State University, NC, USA. The fertilization experiment was initiated in spring 2006 for studying the impacts of fertilization rates on bentgrass growth and organic matter buildup in soil. Sixteen-field plots, each occupying ~5.6 m2 and representing one of four N treatments, were arranged into four blocks based on a randomized block design. The N treatments were an unfertilized control and three rates of N application: 195, 244, and 305 kg N ha−1 yr−1. Fertilizers were applied as a 20–20–20 liquid fertilizer on a bi-weekly basis from June through September using a backpack sprayer (Pro-spray, Cleveland, OH) and as a granular 15– 15–15 IBDU in October, November, February, March, and April using a hand-held shaker. Herbicides, fungicides and insecticides were also applied for preventative controls of weeds, fungal pathogens and insects. Irrigation was provided every week but varied in volume from 0.9 cm to 9 cm per plot dependent on weather and turfgrass growth phase. Bentgrass was mown to 0.30 cm–0.46 cm, with a greater height during environmentally stressful periods in summer and grass clippings were always removed. Topdressing sand was applied with a drip spreader (Gandy, Owatonna, MN) every 2–3 weeks from March through November at a rate of 5.38 m3 ha−1 based on USGA recommendations. A push broom was used to incorporate the topdressing sand into the turf canopy. During the period from spring 2006 to August 2007, grass clipping weights and N in grass tissue were measured in six sampling dates and were found to increase significantly with fertilization rates. Soil organic matter contents in 0–2.54 cm depth and 2.54–7.62 cm depth were also measured in seven sampling dates. Generally, soil organic matter content was greater in 0–2.54 cm depth than 2.54–7.62 cm depth and the

differences in soil organic matter content among fertilization treatments were more pronounced in 0–2.54 cm depth. Effects of fertilization rates on clipping production, N in grass tissue and soil organic matter content were independent of our sampling times. Soils were sampled by coring technique in September 2007, approximately two weeks after a scheduled fertilization. This sampling time allowed us to examine the consequence of one-year-long fertilization treatments. In addition, this sampling time minimized the impacts of newly-produced plant biomass, such as root exudates on soil properties because bentgrass grew slowly in September, as shown by the low weight of grass clippings. A deep soil sampling was made to further minimize the impacts of belowground plant biomass on soil properties. Six cores (2 cm in diameter × 12 cm in length) were randomly taken from each plot and then mixed to represent a composite soil sample. After sieving (b2 mm) and removal of visible roots and plant residues, soil samples were stored at 4 °C until analyses of soil and microbial properties. 2.2. Soil properties Total soil C and N were determined by dry combustion using Perkin-Elmer Series II CHNS/O-2400 analyzer (Perkin Elmer Corp., + Norwark, CT, USA). Soil inorganic N (NO− 3 and NH4 ) was extracted with 1 M KCl and then analyzed colorimetrically using a Lachat flowinjection auto-analyzer (Lachat Instruments, Mequon, WI, USA). Soil pH was measured in soil slurry with a soil (g) to water (ml) ratio of 1:2.5. Chemical compositions (i.e., functional groups) of extractable and soil organic matter were assessed with Fourier transform infrared (FTIR) spectroscopy. Fifteen grams of moist soil were extracted with 75 ml of 0.5 M K2SO4. After shaking at 250 rpm for 30 min, the soil slurry was centrifuged at ~ 2000 ×g for 10 min. The liquid and solid fractions were separated, freeze-dried, and an aliquot (10 mg) was mixed with 0.5 g KBr, ground to fine powder, and pressed into a translucent pellet. The pellets were scanned from wavenumber 4000 to 400 cm−1 with a Nexus 470 FTIR spectrophotometer (Thermo Nicolet Corporation, Madison, WI, USA). Chemical functional groups, as defined by Johnston and Aochi (1996), were identified and semiquantified using the ratio of peak height at a certain wavenumber to the peak height at the polysaccharide peak near 1060 cm−1 (Gressel et al., 1995b). 2.3. Soil microbial biomass, activity, and composition Microbial biomass C and N were determined by the chloroform fumigation method (Brookes et al., 1985; Vance et al., 1987) and extraction coefficients 0.38 and 0.54 were used for biomass C and N calculation, respectively. Carbon and nitrogen mineralization potentials were measured as a cumulative production of CO2 and inorganic N over a two-month incubation as described previously (Shi et al., 2006b). Activities of soil enzymes including β-glucosidase, N-acetyl-βglucosiminidase, cellulase, chitinase, and peroxidase were determined using colorimetric assays. Glucosidase and N-acetyl-β-glucosaminidase activities were determined using p-nitrophenol-glucopyronoside and p-nitrophenol-glucosiminide as substrates, respectively (Parham and Deng, 2000; Turner et al., 2002). Cellulase activity was determined using carboxymethyl cellulose (i.e., CM-cellulose) as the substrate according to the method of von Mersi and Schinner (1996). Chitinase activity was measured via the appearance of N-acetyl-glucosamine after soil incubation with chitin (Rössner, 1996). Peroxidase activity was measured using L-dihydroxy-phenylalanine (L-DOPA) as the substrate (Saiya-Cork et al., 2002). Enzyme activities were expressed as pkat g−1 soil with one kat defined as 1 mol of product appearance or substrate disappearance per second.

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Microbial community composition was examined via DNA fingerprinting. For each soil sample, DNA was extracted from 0.6 g moist soil using the FastDNA SPIN Kit (Qbiogene, Inc. Carlsbad, CA). Extracted DNA was of sufficient purity for direct use in polymerase chain reaction (PCR) amplifications. PCR amplification of bacterial gene fragments was accomplished using GC-clamped primer pair Eub357-GC and Eub518 targeting the 16S rRNA gene (Muyzer et al., 1993). PCR was carried out in a 50 μl solution containing 2 μl of extracted DNA (~3 ng μl−1), 5 μl of PCR buffer (10X), 1.5 μl of MgCl2 (50 mM), 1 μl of BSA (10 mg ml−1), 1 μl of deoxynucleoside triphosphates (10 mM), 1 μl of each primer (10 μM), and 1 μl of Taq DNA polymerase (1U μl−1) (Apex Red Taq, Genesee Scientific Inc., San Diego, California, USA). The reaction was initiated by a 3 min denaturation at 95 °C, followed by 25 cycles of 1 min denaturation at 94 °C, 45 s annealing at 55 °C, and 2 min extension at 72 °C, and ended after 7 min of final extension at 72 °C. Fungal gene fragments were amplified with a nested PCR protocol targeting the 18S rRNA gene (Oros-Sichler et al., 2006). Extracted DNA was first amplified with primer pair NS1 and EF3 in a 25 μl PCR reaction using the same ingredient concentrations as above except that 1.8 μl of MgCl2 (50 mM) was used and 0.5 μl of dimethyl sulfoxide was added. Thermal cycling conditions were the same as the bacterial amplification except that the annealing temperature was changed to 48 °C and the cycle number was 20. Then, 1 μl of amplified product from the first PCR reaction was amplified with the second primer pair NS1 and GC-clamped FR1 using the same reaction and thermal cycling conditions as the first PCR except that the volume of the reaction was increased to 50 μl. Negative controls from the first PCR reaction were carried over to the second PCR. Denaturing gradient gel electrophoresis (DGGE) was performed for both 16S rRNA and 18S rRNA gene amplicons using BioRad DCode system (BioRad, Hercules, CA, USA) following the methods of Muyzer et al. (1993) and Oros-Sichler et al. (2006), respectively. Approximately 400 ng of PCR product from each soil sample was loaded to the DGGE gel, except ~150 ng due to insufficient PCR product from a control sample being used for the 16S rRNA DGGE gel. After DGGE, gels were stained using 1:10,000 dilution of SYBR green (Cambrex Bio Science Rockland Inc., Rockland, ME, USA) and visualized and photographed using GeneSnap system (Syngene, Frederick, MD, USA). Pattern and intensity of bands were analyzed with GeneTools Software (Syngene, Frederick, MD, USA).

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Beach, OR, USA). For fair comparisons, the intensity of each band was normalized by the amount of PCR product loaded into the DGGE gel. 3. Results 3.1. Soil properties, microbial biomass, and C and N mineralization Soil organic C, inorganic N, and pH differed significantly among fertilization treatments (Table 1). In comparison with unfertilized control, fertilized plots contained ~10% higher soil organic C and onefold higher soil inorganic N. Nitrogen fertilization reduced soil pH and the acidification was positively related to N fertilization rates (Table 1). However, there were no treatment effects for total soil N, microbial biomass C and N, C mineralization, or N mineralization (Table 1). FTIR profiles revealed differences in the chemical composition of soil organic matter between solid and extractable fractions (Fig. 1), but similarities among treatments as evidenced by the statistical analysis of peak height ratios of major peaks (data not shown). Peaks in both solid and liquid fractions included C–O stretching of polysaccharides represented in peaks around 1100 cm−1; C=O stretching of carboxylic acids, amides, quinones, and ketones around 1600 cm−1; and O–H stretching of carboxylic acids, phenols, alcohols and/or N–H stretching of amines and amides around 3450 cm−1. Extractable fraction possessed several peaks at 2080–2270 cm−1 corresponding to C`N or N`N triple bond in configurations such as acetylide, isocyanate, isonitrile and nitrile (Bouchet-Fabre et al., 2005; Cataldo, 1998). Solid fraction contained C`N or N`N peak only around 2080 and additionally it had a major aliphatic C–H stretching at ~ 2920 cm−1 and several peaks at 1850–2000 cm−1. 3.2. Soil enzyme activities Nitrogen fertilization had no effect on peroxidase activity, but significantly changed the activities of hydrolytic enzymes including glucosidase, N-acetyl-glucosaminidase, cellulase, and chitinase (Fig. 2). Generally, soil enzyme activities peaked with N fertilization at 195 kg N ha−1 yr−1. Enzyme activities were significantly reduced from the peak values by ~40, 65, 20, and 25% for glucosidase, N-acetylglucosaminidase, cellulase, and chitinase, respectively, when the fertilization rate reached 305 kg N ha−1 yr−1. Soil hydrolytic enzyme activities in the highest N fertilization plots were comparable to or lower than those in unfertilized controls (Fig. 2).

2.4. Statistical analysis

3.3. Bacterial and fungal community compositions

Analysis of variance (ANOVA) for the randomized block design was used to examine whether N fertilization had significant effects on soil and microbial properties. Differences between treatment means were tested for significance with the Waller–Duncan K-ratio t-test (SAS Institute Inc., 2001, NC, USA). Fertilization effects on microbial community composition (e.g., pattern and intensity of DGGE bands) were evaluated with non-metric multidimensional scaling (NMS) analysis, followed by pair-wise comparisons using multi-response permutation procedure (MRPP) (PC-ORD, MjM software, Gleneden

Banding patterns of bacterial and fungal communities were generally similar among N fertilization treatments, but there were some minor differences (Fig. 3). For example, several bands above the band “a” appeared mainly in the 244 kg N ha−1 yr−1 treatment (Fig. 3A). Intensity of band “c” seemed similar for various N treatments, but the intensity of band “b” was stronger in unfertilized controls than fertilized treatments (Fig. 3B). NMS analysis revealed little divergence of bacterial and fungal communities between different rates of fertilization, but great difference

Table 1 Selected soil chemical and microbial properties in bentgrass putting greens unfertilized or fertilized with synthetic N. Total soil C

Total soil N

mg C or N g−1 soil Unfertilized Low Middle High

3.60b 3.95a 3.98a 3.85a

MBC

MBN

Inorganic N

Cmin

Nmin

pH

9.9a 8.0a 6.9a 7.8a

2.2c 3.7b 4.6a 3.9b

146.7a 172.3a 155.1a 155.5a

9.2a 10.4a 8.7a 8.0a

6.9a 6.6b 6.3c 6.1d

μg C or N g−1 soil 0.2a 0.2a 0.2a 0.2a

44.9a 46.4a 44.0a 41.6a

MBC and MBN represent microbial biomass C and N, respectively. Cmin and Nmin represent the mineralization potential of soil organic C and soil organic N, respectively. Different letters within a column indicate significant differences of the mean values for n = 4 (Waller t-test, P b 0.05).

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4. Discussion 4.1. Soil microbial and biochemical attributes as affected by N fertilization rates

1170 1060

Absorbance

1610 2150 2080 2210

1080 1150

2270

3440

1610 1880 2000

3450 2920

2080

4000

3000

2000

1000

Wavenumber (cm-1) Fig. 1. FTIR spectra of freeze-dried liquid (top) and solid (bottom) fractions after 0.5 M K2SO4 extraction of soil fertilized with 305 kg N ha−1 yr−1. Because FTIR spectra from all the fertilization treatments were very similar, this profile is considered representative of all samples.

between unfertilized and fertilized treatments (Fig. 4). MRPP analysis confirmed that fungal communities were significantly different between unfertilized and all fertilized plots (“A” value = 0.11–0.15, P b 0.05). However, for bacterial communities significant differences were only confirmed between the control and the high rate of fertilized plots as well as between the high and low rate of fertilized plots (“A” value was 0.16 and 0.08, respectively; P b 0.05).

70 Unfertilized Low Middle High

a

Soil enzyme activity (pkat g-1 soil)

60

ab

50

40

b

a a

b 30

b 20

ab

b

ab b

a ab a b

b

10

0

a a

Glucosidase Glucosaminidase Cellulase

Chitinase

a a

Peroxidase

Fig. 2. Soil enzyme activities in bentgrass putting greens unfertilized or fertilized with synthetic N at 195 (low), 244 (middle), and 305 (high) kg N ha−1 yr−1. Bars represent standard errors of mean values (n = 4). Different letters within a group indicate significant differences between means (Waller t-test, P b 0.05).

Challenged with contemporary environmental issues such as water and air pollution as well as concerns over maintaining putting green quality, decisions as to the appropriate fertilization rate for golf course greens require a holistic consideration of vegetation traits as well as soil quality. Formulation of a minimum set of soil and microbial properties, which are most responsive to fertilization rates and thus their changes can be used to learn about the impacts of fertilization will aid in putting green management. It is generally accepted that soil microbial properties are sensitive to environmental changes and thus may have potentials to diagnose N fertilization impacts. Although soil microbial biomass and its activity measured as CO2 respiration are the most often used biological parameters for the assessment of management impacts, only soil enzyme activities were able to differentiate the rates of N fertilization in our study. These observations were corroborated with those in a hay production field (Iyyemperumal and Shi, 2008). One of the mechanisms that underline the effects of N fertilization on soil enzymes is the microbial resource allocation theory (Allison and Vitousek, 2005; Koch, 1985). When a nutrient is abundant, microbes may shift their resources away from the synthesis of the nutrient-acquiring enzymes. Accordingly, a negative correlation is expected between nutrient availability and the activity of the nutrientacquiring enzymes. This concept appears to be well supported by negative correlations between soil P availability and soil phosphatase activity (Allison and Vitousek, 2005; Olander and Vitousek, 2000). Microbial resource allocation theory also predicts that C-acquiring enzymes will increase in response to fertilization. Indeed, in N-limited ecosystems such as forests, an increase in soil available N by fertilization has been found to stimulate C-acquiring enzymes, such as cellulase and glucosidase, but suppress phenol oxidase and peroxidase involved in the oxidation of lignin and soil humus (Gallo et al., 2004; Saiya-Cork et al., 2002; Sinsabaugh et al., 2005). Therefore, we expected that the activities of cellulase and glucosidase would increase by N fertilization, whereas the activities of chitinase, glucosaminidase, and peroxidase would decrease. However, soil β-glucosidase activity was only enhanced by fertilization at the low rate and soil cellulase activity was even suppressed by fertilization at the high rate. Furthermore, N mineralization enzymes were increased by fertilization at the low rate and soil peroxidase activity was independent of fertilization treatments. Our results suggested that mechanisms other than microbial resource allocation regulated soil enzyme activities in turfgrass putting greens. We observed that the activities of all the hydrolytic enzymes declined in response to an increase of fertilization rates from 195 to 305 kg N ha−1 yr−1. This reduction was paralleled with the reduction in soil pH. It is well known that soil pH can affect enzyme activities via its controls on protein ionization and substrate or co-factor availability. Together with other observations (Iyymepeumal and Shi, 2008), our results indicated that when soil pH was reduced by N0.5 units, pH-associated effects on soil enzymes would be apparent. In putting greens with the high rate of fertilization, turfgrass production could be greatly stimulated, as shown by the field measurement of clipping weights. On the other hand, high fertilization rate-induced low activities of soil enzymes might cause the slowdown of decomposition of soil organic matter. As a consequence, fertilization at the high rate could accelerate the buildup of soil organic matter in putting greens. In fact, organic matter content in the 0–2.54 cm soil depth was about 20% greater in putting greens fertilized with 305 kg N ha−1 than those with 195 kg N ha−1 (data no shown). With soil depth increase, the difference in soil organic matter content between the two fertilization rates reduced greatly. The sampling depth-associated dilution effect

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219

Fig. 3. Denaturing gradient gel electrophoresis (DGGE) fingerprinting for (A) 16S rRNA gene fragments, i.e., bacterial community, and (B) 18S rRNA gene fragments, i.e., fungal community, in bentgrass putting greens unfertilized (lanes 1–4) or fertilized with synthetic N at 195 (lanes 5–8), 244 (lanes 9–12), and 305 (lanes 13–16) kg N ha−1 yr−1.

might explain why we did not observe the difference in soil organic matter content in the top 12 cm depth among putting greens fertilized with low, middle, and high rates. Accumulation of soil organic matter in putting greens is undesirable because it makes greens less permeable to water and contributed to low oxygen in the root zone (Carrow, 2003). Our study suggested that fertilization rates around 200 kg N ha−1 yr−1 could help to minimize organic matter buildup.

A

1.5

Unfertilized Low Middle High

2nd Axis (62.4%)

1.0

0.5

0.0

-0.5

-1.0

-1.5 -0.8

-0.6

-0.4

-0.2

0.0

0.2

0.4

0.6

0.8

1st Axis (18.8%)

B

4.2. Chemical compositions of soil and extractable organic matter as affected by N fertilization

1.5

2nd Axis (62.3%)

1.0

0.5

0.0

-0.5

-1.0

-1.5 -0.8

-0.6

-0.4

-0.2

0.0

0.2

Chronic N addition has been shown, in some cases, to significantly reduce microbial biomass and activity (Bowden et al., 2004; Burton et al., 2004; Treseder, 2008). In our study, however, no significant changes in biomass nor carbon and nitrogen mineralization could be observed between treatments. Via a meta-analysis using 82 published field studies, Treseder (2008) reported that microbial biomass declined 15% on average under N fertilization. However, the author found that the degree of reduction was dependent on the rate and duration of fertilization and significant reduction in biomass occurred only at high rates and prolonged duration of fertilization. Apparently, fertilization treatments of slightly over one year were insufficient to generate consequences in microbial biomass and activity. In addition, soil sampling to 12 cm depth might dilute the possible differences occurring in the topmost soil. Nevertheless, our results indicate that these microbial attributes would be ineffective to diagnose whether an N fertilization rate is suitable for a given ecosystem during its initial implementation. Although we expected changes in the microbial community composition as a function of N fertilization rates as observed elsewhere (Frey et al., 2004; Zhong and Cai, 2007), the differences were found only consistently between unfertilized and fertilized plots. It is possible that shifts in the community due to fertilization rates were minor in nature and that DGGE was insensitive to detect these shifts.

0.4

0.6

0.8

1st Axis (24.7%) Fig. 4. Non-metric multidimensional scaling (NMS) analysis of DGGE fingerprints for (A) bacterial community, and (B) fungal community in bentgrass putting greens unfertilized or fertilized with synthetic N at 195 (low), 244 (middle), and 305 (high) kg N ha−1 yr−1. Bars represent standard errors of mean values (n = 4).

Produced constantly from the depolymerization of soil organic matter and also serving as C and nutrient sources for microbial growth, extractable soil organics can be dynamic. For example, carbohydrates and amino acids can turn over in hours (van Hees et al., 2005). Deciphering the chemical composition of extractable and recalcitrant soil organics may help understand N fertilization impacts on organic matter decomposition. However, FTIR did not seem sensitive enough to differentiate between fertilization treatments. Interestingly, several triple-bond peaks between 2080 cm−1 and 2270 were detected in both extractable and solid soil fractions. FTIR spectra of another putting green soil also revealed a prominent peak at ~2100 cm−1 (Li and Gaussoin, 2008). However, peaks at these wavenumbers were absent in FTIR profiles of forest litters or soils (Chapman et al., 2001; Gressel et al., 1995a,b; Priha et al., 2001), arable soils (Ding et al., 2002; Ellerbrock et al., 1999; Garcia-Gil et al., 2004; Gressel et al., 1995a), and golf course fairway soils (Shi et al., 2006a). Triple bonds between C and N and between C and C atoms are

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characteristic of many man-made chemicals, such as pesticides and herbicides. Indeed, pesticides with triple-bond ingredients (e.g., ambda cyhalothrin as Scimitar and chlorothalonil as Draconil) had been regularly applied to our putting greens. FTIR detection of these compounds in putting greens rather than in arable soils or golf course fairways reflects the extreme management of putting greens as compared with other systems. Despite reports that efflux of pesticides from putting greens are negligible (Kenna, 1995; Wu et al., 2002a,b) and that both lambda cyhalothrin and chlorothalonil have low persistence in soil (Agnihotri et al., 1997; Kenna, 1995), our study suggests pesticide metabolites may persevere in putting green soils or turf thatch. Detection of aliphatic C–H compounds in the solid fraction (peak at ~ 2920 cm−1) raises questions as to their impact on putting green water permeability since aliphatic hydrocarbons are thought to contribute to soil water repellency (Horne and McIntosh, 2000). Although no clear trends were seen for the relationship between N fertilization rates and hydrocarbons levels, FTIR may still be a useful tool to investigate the role of C–H compounds in putting green water repellency. 4.3. Implications Fertilization can affect bentgrass productivity as shown by the increase in clipping biomass. Thus, soil C input via grass clippings, root exudates, and root biomass likely increases with the fertilization rate. Although grass clippings were removed from the putting greens, belowground primary production could help raise soil organic matter content as shown by the field measurement over seven sampling dates. However, the differences in soil organic matter content among fertilization treatments occurred mainly in the top 2.5 cm soil depth. These field observations suggested that soil sampling to 12 cm depth could mask differences in chemical and biological properties in the topmost soil. Perhaps, only soil properties with great changes can be detected when deep soil sampling is made. Indeed, changes in microbial biomass and potential mineralization rates of soil C and N were statistically insignificant among low, middle, and high rates of fertilization, although soil microbial biomass and mineralization tended to be numerically greater in putting greens with the low rate fertilization. However, we did observe that soil pH and soil enzyme activity were different among the rates of fertilization, indicating that soil enzyme activity was more sensitive than the other biological parameters in response to N fertilization rates. Soil hydrolytic enzymes are imperative for the depolymerization of complex C and N compounds, such as cellulose, the major component of plant primary production. The high activities of soil hydrolytic enzymes at the low fertilization rate can help accelerate the degradation of soil organic matter and plant litters. Thus, soil organic matter buildup in putting greens at the low rate of fertilization can be slow as compared to the high rate of fertilization. Furthermore, when soil enzyme activities are enhanced at the low rate of fertilization, the mineralization rate of soil organic N can be increased, thereby reducing the need for synthetic N fertilizers. This will improve the N use efficiency of putting greens and thus reduce N loss via leaching and gas emission. 5. Conclusions Of the measured microbial properties, only hydrolytic enzyme activities responded to the different N fertilization rates. The more traditionally used metrics, such as microbial biomass and respiration, seemed irrelevant to the impact assessment. Therefore, caution should be taken when using these properties to assess management influences on belowground biology. Hydrolytic enzyme activities can be a valuable metric to assess N fertilization impacts on soil, especially

during early-year implementation. There appears to be a threshold rate of N fertilization below which soil enzyme activities can be increased. However, high rates of N fertilization may generate negative effects on soil enzyme activity and, therefore, do not benefit soil C and nutrient cycling. Although our study is conducted in turfgrass systems, the basic conclusions that N fertilization at high rates could suppress soil enzymes involved in soil C and N cycling may be applicable to other arable and managed ecosystems where fertilization is required for primary production. Acknowledgements The senior author, Yueyan Liu was financially supported by the China Scholarship Council for this study in the USA. We thank David Goodman for helping in the soil sample collections. Anonymous reviewers provide constructive comments for helping us improve the manuscript. References Agnihotri, N.P., Gajbhiye, V.T., Srivastava, K.P., 1997. Persistence of lambda-cyhalothrin in soil. Indian J. 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